0x60Lesson 7 of 10

Tool use and agents

Let a model call functions, loop over tool results like an agent, and keep that loop safe.

22 min 5-question quiz 2 code exercises

By the end of this lesson you can

Follow the tool-calling loop between an app and a model
Validate and dispatch tool calls safely
Bound an agent loop and require confirmation for risky actions

An LLM can only produce text - but that text can be a structured request to call a tool. The application describes available tools (name, description, JSON schema for arguments); the model replies with a tool call; your code runs the function and sends the result back; the model continues. Protocols like MCP standardize how tools are offered.

An agent is that loop running until the task is done: the model plans, calls tools, reads results and decides what next - searching, editing files, running tests.

Try it

One tool call, step by step

Follow a weather question through the tool-calling loop. Predict the marked steps.

Message 1 of 7Predicted 0/0

User

Application

Model

Weather API

dispatch.py

1import json
2TOOLS = {"add": lambda a, b: a + b}
3call = json.loads('{"tool": "add", "arguments": {"a": 2, "b": 3}}')
4print(TOOLS[call["tool"]](**call["arguments"]))

Output

Key takeaways

Models request tool calls as structured text; applications execute them.
An agent loops: think, call tools, read results, repeat - until done or stopped.
Validate arguments, cap steps, least privilege, confirm risky actions, distrust tool output.

Lesson quiz

5 questions · pass with 4 correct · up to 50 XP

Passing this quiz completes the lesson and keeps your streak going. Questions you miss come back in review sessions later.

Practice: write Python

Write Python in the editor and run it against sample inputs. Python runs locally in your browser using a WebAssembly runtime.

Exercise 1

Dispatch tool calls safely

+25 XP

Each line is a JSON tool call {"tool": ..., "arguments": {...}}. Only add(a, b) (two numbers) and get_forecast(city) (from the FORECASTS table) exist. Print the result, or error: unknown tool NAME, error: bad arguments (wrong names or types), or error: no forecast for CITY.

Five calls

main.py

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Python runs in a sandboxed browser worker with a 60 second time limit. Its runtime loads from the Pyodide CDN; your code stays in this browser.

Exercise 2

Run a bounded agent loop

+25 XP

Line 1 is the step limit. Each following line is the model’s next reply, as JSON: either {"tool": "search", "query": "..."} or {"answer": "..."}. Run the loop:

for a search, look the query up in INDEX (or no results) and print step N: search(QUERY) -> RESULT;
for an answer, print answer: TEXT and stop;
if the step limit is reached before an answer, print stopped: step limit reached.

Answers in time
Runs out of steps

main.py

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Python runs in a sandboxed browser worker with a 60 second time limit. Its runtime loads from the Pyodide CDN; your code stays in this browser.

Questions about this lesson

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